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New Morbidity and Comorbidity Scores based on the Structure of the ICD-10

Measures of morbidity and comorbidity are frequently used for the control of confounding, particularly in health services research. Several proposals for those measures are defined with ICD-coded diagnoses available in hospital routine data. However, a measure that makes use of the ICD structure is...

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Autores principales: Stausberg, Jürgen, Hagn, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4677989/
https://www.ncbi.nlm.nih.gov/pubmed/26656501
http://dx.doi.org/10.1371/journal.pone.0143365
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author Stausberg, Jürgen
Hagn, Stefan
author_facet Stausberg, Jürgen
Hagn, Stefan
author_sort Stausberg, Jürgen
collection PubMed
description Measures of morbidity and comorbidity are frequently used for the control of confounding, particularly in health services research. Several proposals for those measures are defined with ICD-coded diagnoses available in hospital routine data. However, a measure that makes use of the ICD structure is missing. Objective of this work was to elaborate the power of the ICD structure for defining morbidity and comorbidity measures. Routine data from three German hospitals with inpatients discharged 2008 were used for model development; routine data from 36 German hospitals with inpatients admitted and discharged 2010 were used for model evaluation. Two different risk models were developed, one based on ICD-10 chapters, the other based on ICD-10 groups. The models were transformed into sum scores using whole-number weights. Models and scores were compared with the Charlson Index and the Elixhauser Comorbidities using the receiver operating characteristic. Dependent variable was hospital death. Logistic regression was used to derive the new models. Charlson Index and Elixhauser Comorbidities were mapped to the German ICD-10. According to the receiver operating characteristic, the quality of the measures based on the structure of the ICD-10 was superior compared with the Charlson Index and the Elixhauser Comorbidities. The best result was achieved with the measure based on ICD-10-groups with an area under curve of 0.910 (95% confidence interval = 0.907–0.913). The sum scores showed a comparable performance. The developed new measures may be used to control for confounding.
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spelling pubmed-46779892015-12-31 New Morbidity and Comorbidity Scores based on the Structure of the ICD-10 Stausberg, Jürgen Hagn, Stefan PLoS One Research Article Measures of morbidity and comorbidity are frequently used for the control of confounding, particularly in health services research. Several proposals for those measures are defined with ICD-coded diagnoses available in hospital routine data. However, a measure that makes use of the ICD structure is missing. Objective of this work was to elaborate the power of the ICD structure for defining morbidity and comorbidity measures. Routine data from three German hospitals with inpatients discharged 2008 were used for model development; routine data from 36 German hospitals with inpatients admitted and discharged 2010 were used for model evaluation. Two different risk models were developed, one based on ICD-10 chapters, the other based on ICD-10 groups. The models were transformed into sum scores using whole-number weights. Models and scores were compared with the Charlson Index and the Elixhauser Comorbidities using the receiver operating characteristic. Dependent variable was hospital death. Logistic regression was used to derive the new models. Charlson Index and Elixhauser Comorbidities were mapped to the German ICD-10. According to the receiver operating characteristic, the quality of the measures based on the structure of the ICD-10 was superior compared with the Charlson Index and the Elixhauser Comorbidities. The best result was achieved with the measure based on ICD-10-groups with an area under curve of 0.910 (95% confidence interval = 0.907–0.913). The sum scores showed a comparable performance. The developed new measures may be used to control for confounding. Public Library of Science 2015-12-14 /pmc/articles/PMC4677989/ /pubmed/26656501 http://dx.doi.org/10.1371/journal.pone.0143365 Text en © 2015 Stausberg, Hagn http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Stausberg, Jürgen
Hagn, Stefan
New Morbidity and Comorbidity Scores based on the Structure of the ICD-10
title New Morbidity and Comorbidity Scores based on the Structure of the ICD-10
title_full New Morbidity and Comorbidity Scores based on the Structure of the ICD-10
title_fullStr New Morbidity and Comorbidity Scores based on the Structure of the ICD-10
title_full_unstemmed New Morbidity and Comorbidity Scores based on the Structure of the ICD-10
title_short New Morbidity and Comorbidity Scores based on the Structure of the ICD-10
title_sort new morbidity and comorbidity scores based on the structure of the icd-10
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4677989/
https://www.ncbi.nlm.nih.gov/pubmed/26656501
http://dx.doi.org/10.1371/journal.pone.0143365
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